Massive multiple input, multiple output (MIMO) has recently become a topic of great interest in the industry. In massive MIMO, the number of base station antennas can reach dozens or even hundreds. The main promises of massive MIMO are (i) simplified signal processing in the multi-user case, since simple conjugate beamforming provides quasi-optimum performance, and (ii) drastically reduced energy consumption, due to the high beamforming gain, and thus the possibility of lowering the transmit power while still retaining a high signal-to-noise ratio (SNR). However, these advantages are counteracted, in practice, by the increased hardware complexity associated with having many antennas and many associated up/down conversion chains, and by the increased energy consumption due to all that hardware.
A popular method for reducing MIMO complexity while retaining most of its benefits is antenna selection, where a subset of size L taken from the set of the N available antenna signals is selected and connected, via a switch, to L (L<N) radio-frequency (RF) chains. For the transmit case, each RF chain includes a modulator, digital-to-analog converter (DAC), and a power amplifier and each transmit antenna requires an RF chain; similar statements can be made for the receive case. This method has shown to provide the same diversity order as a full-complexity MIMO system. However, this method does not provide the same amount of beamforming gain, and thus shows reduced performance in particular in channels with small angular spread, as typically occur in cellular systems. To remedy this situation, a pre-processing of the received signal by an RF preprocessing matrix can be performed, which essentially transforms the received signals from the antenna space into a beamspace. The switch then subsequently performs “beam selection” instead of antenna selection. The first proposal of this method used a fixed matrix, namely a (spatial) FFT matrix, for the preprocessing. Another proposal also considers a simplified structure in which each RF chain is connected, via adaptive phase shifters to a fixed subset of antenna elements. In the present description, the optimum precoding in baseband and optimum values of the phase shifters are discussed.
For the general preprocessor structure, others have shown that if the preprocessing can be adapted based on instantaneous channel state information, then close-to-optimum performance can be maintained even with a small number of RF chains. However, such a fast adaptation is not necessarily easy or desirable, both due to the necessary speed of the hardware reconfiguration, and (for the transmit case) due to the required speed and overheads of the required feedback. Others have investigated the case where the preprocessing matrix is adapted only based on the average CSI, which changes on a much slower time scale, and which is usually known at transmitter and receiver (note that for FDD systems, the instantaneous CSI at uplink and downlink is usually uncorrelated, while the average CSI is essentially identical. However, the determination of the entries of the preprocessing matrix can suffer from two major drawbacks: (i) it is based on an approximation, so use of the computed parameters may result in significant performance loss, and (ii) it is not easily generalized to the multi-user case.
Performance of antenna selection in correlated channels has been analyzed in terms of the symbol error probability. There has been disclosure regarding the selection of a single antenna, and a system has been disclosed where the selection is based on the average, not the instantaneous, channel characteristics. There has also been disclosure of antenna selection in channels where the correlation comes from a Rician component, not from small angular spread of Rayleigh-fading components.